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-/https://github.com/berriai/litellm/issues/12875
GitHub · issue

#12875 [Bug]: LiteLLM_Config table is overwriting newly deployed config

  • State: open
  • Author: @ma-armenta
  • Labels: bug, mlops user request

### What happened?

I noticed that new proxy configs were not getting picked up, specifically general_settings, but I suspect it will apply to most of what inside table LiteLLM_Config.

In litellm/proxy/proxy_server.py, the function_update_config_fields is pulling in values from config and overwriting the newly deployed values.

That or the initial update, at deployment time, of that table is just not happening and previous values stay behind, and then the new values get overwritten.

I confirmed this behavior by manually deleting the general_settings row, rollout restating, and then the new values got populated.

### Relevant log output

```shell n/a ```

### Are you a ML Ops Team?

Yes

### What LiteLLM version are you on ?

v1.74.3-stable.patch.3

### Twitter / LinkedIn details

https://www.linkedin.com/in/maarmenta/

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vote history (3 events)
#0 of 0 · 31d18h49m16s ago — entered · #import:https:::github.com:berriai:litellm post #1922
12875 requires tracing configuration precedence, persistence, startup synchronization, and rollout behavior across proxy state and storage, with substantial regression risk; 30657 is comparatively localized provider/model routing work with focused tests.
The right issue is harder because it requires tracing configuration precedence, persistence, deployment synchronization, and regression behavior across the proxy lifecycle. The left issue is a narrowly scoped catalog metadata correction with straightforward validation.
#0 of 0 · 31d17h59m40s ago — current · #import:https:::github.com:berriai:litellm post #2735
The right-side task has broader cross-cutting scope: it involves persistence semantics, deployment lifecycle ordering, backward compatibility, and regression testing. The left-side task is comparatively localized to provider/model compatibility handling and validation.
discussed in #import:https:::github.com:berriai:litellm

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